IOT BASED UNDERGROUND CABLE FAULT DETECTOR · PDF fileIOT BASED UNDERGROUND CABLE FAULT...

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International Journal of Mechanical Engineering and Technology (IJMET) Volume 8, Issue 8, August 2017, pp. 1299–1309, Article ID: IJMET_08_08_132

Available online at http://www.iaeme.com/IJMET/issues.asp?JType=IJMET&VType=8&IType=8

ISSN Print: 0976-6340 and ISSN Online: 0976-6359

© IAEME Publication Scopus Indexed

IOT BASED UNDERGROUND CABLE FAULT

DETECTOR

Mr. N. Sampathraja

Assistant Professor, PSG College of Technology, Coimbatore, Tamil Nadu India

Dr. L. Ashok Kumar

Professor, PSG College of Technology, Coimbatore, Tamil Nadu India

Ms. V. Kirubalakshmi and Ms. C. Muthumaniyarasi

Student, PSG College of Technology, Coimbatore, Tamil Nadu India

Mr. K. Vishnu Murthy

Assistant Professor, Sri Krishna College of Technology, Coimbatore, Tamil Nadu India

ABSTRACT:

Underground cables are prone to a wide variety of faults due to underground

conditions, wear and tear, rodents etc. Diagnosing fault source is difficult and entire

cable should be taken out from the ground to check and fix faults. The project work is

intended to detect the location of fault in underground cable lines from the base

station in km using a PIC16F877A controller. To locate a fault in the cable, the cable

must be tested for faults. This prototype uses the simple concept of Ohms law. The

current would vary depending upon the length of fault of the cable. In the urban areas,

the electrical cables run in underground instead of overhead lines. Whenever the fault

occurs in underground cable it is difficult to detect the exact location of the fault for

process of repairing that particular cable. The proposed system finds the exact

location of the fault. The prototype is modeled with a set of resistors representing

cable length in km and fault creation is made by a set of switches at every known

distance to cross check the accuracy of the same. In case of fault, the voltage across

series resistors changes accordingly, which is then fed to an ADC to develop precise

digital data to a programmed PIC IC that further displays fault location in distance.

The fault occurring distance, phase, and time is displayed on a 16X2 LCD interfaced

with the microcontroller. IoT is used to display the information over Internet using the

Wi-Fi module ESP8266.A webpage is created using HTML coding and the

information about occurrence of fault is displayed in a webpage.

Keywords: Underground Cable, Fault Location, Location Methods, Microcontroller,

webpage.

Mr. N. Sampathraja, Dr. L. Ashok Kumar, Mr. K. Vishnu Murthy, Ms. V. Kirubalakshmi and Ms. C.

Muthumaniyarasi


Cite this Article: Mr. N. Sampathraja, Dr. L. Ashok Kumar, Mr. K. Vishnu Murthy,

Ms. V. Kirubalakshmi and Ms. C. Muthumaniyarasi, Iot Based Underground Cable

Fault Detector, International Journal of Mechanical Engineering and Technology 8(8),

2017, pp. 1299–1309.

http://www.iaeme.com/IJMET/issues.asp?JType=IJMET&VType=8&IType=8

1. INTRODUCTION

Power supply networks are growing continuously and their reliability getting more important

than ever. The complexity of the whole network comprises numerous components that can

fail and interrupt the power supply for end user. For most of the worldwide operated low

voltage and medium voltage distribution lines, underground cables have been used for many

decades. Underground high voltage cables are used more and more because they are not

influenced by weather conditions, heavy rain, storm, snow and pollution. Even though the

Cable manufacturing technology is improving steadily; there are still influences which

may cause cable to fail during test and operation. A cable in good condition and installed

correctly can last a lifetime of about 30 years. However cables can be easily damaged by

incorrect installation or poorly executed jointing, while subsequent third party damage by

civil works such as trenching or curb edging [1,2].

1.1. Types of Faults in Cables

1.1.1. Open Circuit Fault

When there is a break in the conductor of the cable, it is called open circuit fault of the cable.

The open circuit fault can be checked by megger. For this purpose, the three conductors of the

3-core cable at the far end are shorted and earthed. Then resistance between each conductor

and earth is measured by a megger. The megger will indicate zero resistance in the circuit of

the conductor that is not broken. However, if the conductor is broken, the megger will

indicate infinite resistance in its circuit.

1.1.2. Short Circuit Fault

When two conductors of a multi-core cable come in electrical contact with each other due to

insulation failure, it is called short-circuit fault. The two terminals of the megger are

connected to any two conductors. If the megger gives zero reading, it indicates short-circuit

fault between these two conductors. The same step can be repeated for other conductors

taking two at a time.

1.1.3. Earth Fault

When the conductor of the cable comes in contact with earth, it is called earth fault or ground

fault. To identify this fault, one terminal of the megger is connected to the conductor and the

other terminal connected to earth. If megger indicates zero reading, it means the conductor is

earthed. The same procedure is repeated for other conductors of the cable [4,6].

This project is used to detect the location of fault in digital way. Locating the faulty point

in an underground cable helps to facilitate quicker repair, improve the system reliability and

reduced outage period. The article has been organised as follows. Section 2 discuss about

different methods used to detect the location of fault in underground cables. Section 3

describes the basic principle of the proposed fault locating method. Section 4 briefly explains

the working of the proposed system with a help of flow chart. Section 5 presents the circuit

which is a prototype model for the proposed system. Section 6 gives the simulation of the

Iot Based Underground Cable Fault Detector


work using Proteus 8.5 Professional software. The section also explains the hardware

implementation and the results. Section 7 Provides conclusion and future scope of the work.

2. LITERATURE SURVEY

2.1 Sectionalizing

This procedure reduces cable reliability, because it depends on physically cutting and splicing

the cable. Dividing the cable into successively smaller sections and measuring both ways with

an ohmmeter or high-voltage insulation resistance (IR) tester enable to narrow down search

for a fault. This laborious procedure normally involves repeated cable excavation [2,8].

2.2. Thumping

When high voltage is supplied to faulty cable, the resulted high current arc makes a noise loud

enough to hear above ground. While this method eliminates the sectionalizing method’s

cutting and splicing, it has its own drawback. Thumping requires a current on the order of tens

of thousands of amps at voltages as high as 25 kV to make an underground noise loud enough

to hear above ground. The heating from this high current often causes some degradation of the

cable insulation. The limit of damage can be reduced by passing minimum required power to

conduct the test [2].

2.3. Time-Domain Reflectometry

The Time domain reflectometer (TDR) is an electronic instrument that uses time domain

reflectometry to characterize and locate faults in metallic cables. The TDR sends a low-

energy signal through the cable, causing no insulation degradation. A theoretically perfect

cable returns that signal in a known time and in a known profile. Impedance variations in a

“real-world” cable alter both the time and profile, which the TDR screen or printout

graphically represents. One weakness of TDR is that it does not pinpoint faults.

2.4. Arc Reflection Method

This method is often referred to as a high voltage radar technique that overcomes the 200 Ω

limitation of low-voltage radar. In addition to the TDR, an arc reflection filter and surge

generator is required. The surge generator is used to create an arc across the shunt fault which

creates a momentary short circuit that the TDR can display as a downward-going reflection.

The filter protects the TDR from the high voltagepulse generated by the surge generator and

routes the low-voltage pulses down the cable. Arc reflection is the most accurate and easiest

pre location method. The fault is displayed in relation to other cable landmarks such as

splices, taps and transformers and no interpretation is required. Arc reflection makes it

possible for the TDR to display “before” and “after” traces or cable signatures. The “before”

trace is the low-voltage radar signature that shows all cable landmarks but does not show the

downward reflection of a high resistance shunt fault. The “after” trace is the high-voltage

signature that includes the fault location even though its resistance may be higher than 200 Ω.

This trace is digitized, stored and displayed on the screen and the cursors are positioned in

order to read the distance to the high resistance fault [8].

2.5. Blavier Test

When a ground fault occurs in a single cable and there is no other cable, then blavier test can

be performed to locate the fault in a single cable. In other words, in the absence of a sound

cable to locate fault in the cable, then measurement of the resistance from one side or end is

called blavier test. Ground fault of a single cable can be located using Blavier’s test. In this


Muthumaniyarasi


kind of test, low voltage supply, an ammeter and voltmeter are used in a bridge network.

Resistance between one end of the cable (Sending End) and earth is measured while “Far

End” is isolated from the earth [2, 8].

3. INTERNET OF THINGS

The evaluation of IoT in the electrical Power Industry transformed the way things performed

in usual manner. IoT increased the use of wireless technology to connect power industry

assets and infrastructure in order to lower the power consumption and cost. The applications

of IoT are not limited to particular fields, but span a wide range of applications such as energy

systems, homes, industries, cities, logistics, heath, agriculture and so on. Since 1881, the

overall power grid system has been built up over more than 13 decades, meeting the ever

increasing demand for energy. Power grids are now been considered to be one of the vital

components of infrastructure on which the modern society depends. It is essential to provide

uninterrupted power without outages or losses. It is quiet hard to digest the fact that power

generated is not equal to the power consumed at the end point due to various losses. It is even

harder to imagine the after effects without power for a minute. Power outages occur as result

of short circuits. This is a costly event as it influences the industrial production, commercial

activities and consumer lifestyle. Government & independent power providers are

continuously exploring solutions to ensure good power quality, maximize grid uptime, reduce

power consumption, increase the efficiency of grid operations and eradicate outages, power

loss & theft. Most importantly, the solution should provide a real-time visibility to customers

on every penny paid for their energy. There is an increasing need of a centralized

management solution for more reliable, scalable, and manageable operations while also being

cost effective, secure, and interoperable. In addition, the solution should enable power

providers and utilities to perform effective demand forecasting and energy planning to address

the growing need for uninterrupted quality power [5].

The goal of IoT is not just only connecting things such as machines, devices and

appliances, but also allowing the things to communicate, exchanging control data and other

necessary information while executing applications. It consists of IoT devices that have

unique identities and are capable of performing remote sensing, monitoring and actuating

tasks. These devices are capable of interacting with one another directly or indirectly. Data

collection is performed locally or remotely via centralized servers or cloud based applications.

These devices may be data collection devices to which various sensors are attached such as

temperature, humidity, light, etc., or they may be data actuating devices to which actuators are

connected, such as relays.

IoT system is composed of three layers: the perception layer, the network layer, and the application

layer as shown in Figure 1. The perception layer includes a group of Internet-enabled devices that can

percept, detect objects, collect systems information, and exchange information with other devices

through the Internet communication networks. Sensors, Global Positioning Systems (GPS), cameras,

and Radio Frequency Identification Devices (RFID) are examples of devices that exist at perception

layer. The network layer is responsible of forwarding data from perception layer to the application

layer under the constraints of devices’ capabilities, network limitation and the applications’

constraints. IoT systems use a combination of Internet and short-range networks based on the

communicated parties. Short-range communication technologies such as Bluetooth and ZigBee are

used to carry the information from perception devices to a nearby gateway. Other technologies such as

Wi-Fi, 2G, 3G, 4G, and Power line Communication (PLC) carry the information for long distances

based on the application. The upper layer is the application layer, where incoming information is



processed to induce insights for better power’s distribution design and management strategies.

Figure 1 Architecture of IoT

3.1 Online Monitoring of Power Lines

As more buildings and areas are being covered with power line systems, the number and

severity of power outages become more serious leading to lower system’s reliability.

Reliability is important as it causes serious negative impacts on public health and economical

systems. Integration of IoTs technology together with the power grid, aims to improve the

reliability of power grids through a continuous monitoring of transmission lines status; in

addition to environmental behaviours and consumers activities to send periodic reports to the

grid control units. The control units process and extract information from the reported data in

order to detect faults, isolate the fault, and then resolve faults intellectually performing energy

restoration in smart grid must take into the account the location criticality of blackouts. For

examples, it is critical to guarantee high reliability for health and industrial systems. The

restoration problem becomes a very complex problem when taking into the consideration the

large number of combinations of switching operations which exponentially increases with the

increase in system’s components. Designing the smart grid in a hierarchical model divides the

problem into multiple control units in charge of restoring power within its region or scope.

This enhances the time needed to process the data and speeds up the restoration process. If

some control units fail to restore energy in some regions within their scope, they forward the

problem to upper levels for better action and handling as higher levels have a larger system’s

view [5].

3.2 Demand-Side Energy Management

Demand-Side Energy Management (DSM) is the change in consumers energy consumption

profiles according to varying electricity price over time, and other payment’s incentives from

utility companies. Demand response is used to minimize consumer’s electricity bill, shift

peak’s load demand, minimize operation cost of the power grid, and minimize energy loss and

greenhouse’s gas emissions. IoT components collect energy requirements of different home

appliances and send them to smart meters. The control unit in smart grid schedules energy

consumption of homes’ appliances according to the user’s preferences in a strategy that

minimizes the electricity bill. The DSM problem can be solved at different levels of the

hierarchical smart grid infrastructure. It can be solved at the level of home premises to

preserve consumers privacy. Also it can be solved at higher levels to generate more effective

scheduling plan that do not only benefit consumers but also the utility company [5].


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3.3 Integration of Distributed Energy Sources

Renewable energy generators are being integrated into today’s power grid because of

environmental reasons, climate change, and its low cost. This reduces emissions of

greenhouse gases that rises the Earth temperature. In recent years, many governments,

organizations, and individuals started to install solar cells and wind turbines to satisfy part of

their power requirements. Germany for example plans fully fulfil their power demands using

renewable energy sources by 2050. IoT technology uses wireless sensors to collect real-time

weather information to help in predicting the energy availability in the near future. Accuracy

of the forecasted power amounts during the next time intervals is crucial for energy

scheduling models. Different strategies and optimization solutions have been developed in

research to efficiently manage renewable energy sources within the smart grid[5].

3.4 Integration of Electric Vehicles

Electric Vehicles (EVs) are used as energy storage devices while they are idle. Also they

provide efficient and clean transportation services. Developing efficient scheduling

techniques for charging and discharging of electric vehicles can potentially lead to reduce

emissions, shave peak load, and increase the used percentage of generated renewable.

Perception devices collect information about electric vehicles identity, battery state, location,

etc, to improve the efficiency of charging and discharging scheduling algorithms [5].

3.5 Smart Homes

The system and appliances include sensors and actuators that monitor the environment and

send surveillance data to a control unit at home. The control unit enables the householders to

continuously monitor and fully control the electrical appliances. It also uses the surveillance

data to predict future activities to be prepared in advance for a more convenient, comfortable,

secure, and efficient living environment [5].

4. PROPOSED SYSTEM

The proposed system is an IoT enabled underground cable fault detection system. The basic

principle behind the system is Ohms law. When fault occurs in the cable, the voltage varies

which is used to calculate the fault distance. The system consists of Wi-Fi module,

Microcontroller, and Real-Time Clock. The block diagram of the fault detection system is

shown in the Figure 2.The power supply is provided using step-down transformer, rectifier,

and regulator. The current sensing circuit of the cable provides the magnitude of voltage drop

across the resistors to the microcontroller and based on the voltage the fault distance is located

[1,2].

Figure 2 Block Diagram of Fault Detection system



5. FLOW CHART

The flow chart of the logic behind the fault detecting system is given in Figure 3. The input

and output ports of Microcontroller, LCD display, RTC and Wi-Fi module of the system are

configured and initialized. When fault occurs (switch is pressed), the fault distance, time and

phase are displayed corresponding to that fault. The above fault information will be displayed

in the webpage using Wi-Fi module [9,10].

6. CIRCUIT DESCRIPTION

The prototype uses resistors to represent the cable length. The resistors RR1 to RR5 represents

R phase of the cable. Similarly RY1 to RY5 and RB1 to RB5 represent Y and B phase of the

cable. RN1 to RN12 are used to represent the neutral lines. To represent the occurrence of fault

in underground cables switches are used. Each phase is connected with a relay which in turn

is connected to Port C of Microcontroller. When there is no fault, the LEDs connected to each

relay glows.

Figure 3 Flow Chart of Fault Detection System

When a switch connected to a particular phase is closed, the LED connected to the

particular phase alone glows. The resistance connected to that particular phase adds up and

the voltage drop thus generated is given to Port A of the Microcontroller. The voltage drop is

converted to distance as per Table 1 and is displayed in the LCD. Additionally, the pin of Port

C connected to that particular LED goes high and the name of the faulted phase is displayed

in the LCD. The cable side circuit diagram is shown in the Figure 4.


Muthumaniyarasi


Figure 4 Cable Side - Circuit Diagram

S.No. Switch Analog Fault ADC

1. SW 1 3.33 V 1 km 682

2. SW 2 3.99 V 2 km 818

3. SW 3 4.28 V 4 km 876

4 SW 4 4.4 V 8 km 909

Table 1 Mapping Table for Fault Identification

Figure 5 Switch Over Connection- Circuit Diagram



The Real Time Clock DS1307 is connected to Port C of the Microcontroller to display the

time at which fault has occurred. For every clock period the time gets incremented. During

fault, SCL pin of RTC synchronizes the data and SDA pin transmits data to the

Microcontroller which is displayed in the LCD. The switch over connection is activated

during fault period of the cable to transmit uninterrupted power supply which is shown in

figure 5.

7. OBSERVATION AND RESULT

The fault detection system is simulated using Proteus 8.5 professional software and the fault

information is displayed in the LCD. The simulation and hardware setup of the fault detection system

are shown in the Figure 6 and Figure 7 respectively. The Fault display message is shown in the table 2.

The work “IoT Based Underground Cable Fault Detector” is an efficient system as it reduces the time

to detect the exact location of fault.

Figure 6 Simulation of the System using Proteus


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Figure 7 Hardware Setup of the System

HARDWARE STATUS

Problem Affected in R Phase in Time 12:04:35PM

Phase Relay switch Over

ring Distance (in km)

R Phase R2 8 km

Y Phase R 0 km

B Phase R 0 km

Table 2 Fault Display Message in the Webpage

8. CONCLUSION

The short circuit fault at a particular distance in the underground cable is located to rectify the

fault efficiently using simple concepts of Ohms law. The work automatically displays the

phase, distance and time of occurrence of fault with the help of PIC 16F877A and ESP8266

Wi - Fi module in a webpage. The benefits of accurate location of fault are fast repair to

revive back the power system, it improves the system performance, it reduce the operating

expense and the time to locate the faults in the field.

9. FUTURE SCOPE

The work can be extended for open circuit fault, short circuit Line to Line Fault (LL) and

double Line to Ground Fault (LLG). The open circuit fault can be detected using a capacitor

in ac circuit which measures the change in impedance and calculate the distance of fault.



REFERENCES

[1] Xiaoning Kang; Xiuda Ma; Shuai Jiang; Xiaoyun Qu, Chao Zhang; Xiaoning Kang;

Xiuda Ma; Shuai Jiang; Xiaoyun Qu 2016 IEEE PES Asia-Pacific Power and Energy

Engineering Conference (APPEEC)

[2] Gilbert Cheung, Yuan Tian, Tobias Neier, Technics of Locating Underground Cable

Faults inside conduits, International Conference on Condition Monitoring and Diagnosis

IEEE (CMD 2016)

[3] Nikhil Kumar Sain, Rajesh Kajla, and Mr.Vikas Kumar, Underground Cable Fault

Distance Conveyed Over GSM, International Organization of Scientific Research Journal

of Electrical and Electronics Engineering, Volume 11, Issue 2, Mar-April 2016.

[4] C.Bharatiraja, S.Jeevananthan, J.L. Munda, A Timing Correction Algorihm based

extended SVM for three level Neutral point clamped MLI in Over Modulation Zone IEEE

Journal of Emerging and Selected topics in Power Electronics.

[5] Manar Jaradat, Moath Jarrah, Abdel Kader Bousselham, Yaser Jararweh, Mahmoud Al-

Ayyoub The Internet of Energy: Smart Sensor Networks and Big Data Management for

Smart Grid, Procedia Computer Science Elsevier, July 2015.

[6] Dhivya Dharani. A and Sowmya. T, Development of a Prototype of Underground Cable

Fault Detector, International Journal Electrical, Electronics, and Computer Systems,

Volume-2, 2014.

[7] Md. Fakhrul Islam, Amanullah M T O, Salahuddin. A. Azad, Locating Underground

Cable Faults: A Review and Guideline for New Development, 2013 IEEE Conference

[8] M.Fonseca_Badillo, L. Negrete_Navarrete, A. Gonzalez_parada, A. Castaneda_Miranda,

Simulation and analysis of underground power cables faults, 2012 Elsevier Procedia

Engineering

[9] Abishek Pandey, Nicolas H. Younan Underground cable fault detection and identification

using Fourier analysis, 2010 IEEE Conference

[10] Tobias Neier, Cable fault location practical experience, HV Technologies, version-1, June

2006.

[11] M.S. Choi, D.S. Lee, and X. Yang, A Line to Ground Fault Location Algorithm for

Underground Cable System, Korean Institute of Electrical Engineers International

Transactions on Power Engineering, pp. 267 – 273, Jun 2005.

[12] K.K. Kuan, Prof. K. Warwick, Real-time expert system for fault location on high voltage

underground distribution cables, IEEE Proceedings-C, Volume. 139, No. 3, MAY 1992.

[13] Ashlesha A. Patil and Dr. S. R. Suralkar. Review on-IOT Based Smart Healthcare System.

International Journal of Advanced Research in Engineering and Technology, 8(3), 2017,

pp 37–42

[14] Snehal R. Shinde, A. H. Karode and Dr. S. R. Suralkar, Review onIOT Based

Environment Monitoring System, International Journal of Electronics and Communication

Engineering and Technology, 8(2), 2017, pp. 103–108

[15] Viswanath Naik.S1 , S.Pushpa Bai1 , Rajesh.P , Mallikarjuna Naik.B, IOT Based Green

House Monitoring System, International Journal of Electronics and Communication

Engineering & Technology (IJECET), Volume 6, Issue 6, June (2015), pp. 45-47

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